1. Field of the Invention
The present invention relates to a technique used to estimate a behavior selection model of a human or other mobile object on the basis of attributes of an individual, attributes of a field, and behavior history including moving trail information. In particular, the present invention relates to a behavior prediction apparatus, a behavior prediction method, and a behavior prediction program used to estimate a behavior selection model in which the movement frequency in the field is taken in as an influence exerted upon the behavior selection of an individual by a movement of a group.
2. Related Art
The model used to predict behavior selection of an individual or a group in a specific field is regarded important in the field of architecture, civil engineering, marketing and so on, and it is under vigorous study. Its main model is the probabilistic utility maximization model having attributes of an individual acting in the field and attributes associated with the field as explanatory variables. As examples, a logit model and a probit model can be mentioned. As application examples of these models, there are route selection conducted by travelers in transportation behavior and selection of purchase commodities conducted by customers (shoppers) in stores and mail-order business.
The conventional behavior selection model is suitable for taking in the influence exerted upon the behavior selection probability by the attributes of the individual and the attributes of the field. However, a model obtained by satisfactorily taking in the influence exerted upon the individual's selection by a movement of a surrounding group, i.e., the effect provided for the field by a crowd is not sufficiently considered. As an example in which the effect provided for the field by the crowd is conspicuous, behavior selection of a customer (shopper) in a retail store can be mentioned. It is considered that the behavior selection of the customer in the store, such as staying in a salesroom, movement between salesrooms and a commodity purchase/non-purchase, is remarkably influenced not only by the attributes of the customer and the attributes of the field such as the salesroom and commodity but also by the behavior of the surrounding group. In the conventional behavior selection model, however, this influence is not taken in satisfactorily, and it cannot be said that the behavior of the customer in the store is sufficiently modeled.